The background description provided herein is for the purpose of generally presenting the context of the disclosure. Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
With advances in computer vision, image processing and digital photography, making 3D models of human faces has attracted increasing interest from researchers and engineers, since 3D face mesh can be used as a basic tool for understanding facial shape, expression and head-pose. Further, 3D face models have more expandability than two dimensional (2D) face models, and enable developers/designers of applications to provide users with richer experiences, e.g., in visual communication and entertainment. However, making a 3D face model from a single image is not an easy task. Further, tracking expressions and head pose of the 3D mesh in a single video stream is an even more challenging problem. Prior art techniques typically require a complex registration step that may require 5-10 minutes, and they tend to be insufficiently robust for out-of-plane rotation. Further, prior art techniques tend to provide coverage for a limited to small sets of face shapes or expressions, and typically, the amount of computational resources required exceed or at least strain the capability of the more resource constrained devices, such as mobile devices like smartphones or computing tablets.